Degradation Product of Sea Cucumber Polysaccharide by Dielectric Barrier Discharge Enhanced the Migration of Macrophage In Vitro.

This study investigated the effect of dielectric barrier discharge (DBD) on sea cucumber polysaccharide (SP-2) and evaluated its anti-inflammatory properties. The SP-2 was depolymerized by applying an input voltage of 60~90 V for 3~9 min. The features of the products were examined using high-performance gel permeation chromatography, HPLC-PAD-MS, and the Fourier transform infrared (FTIR) spectrum. The anti-inflammatory properties of the product were investigated by measuring nitric oxide (NO) release, ROS accumulation, and cell migration using RAW264.7 cells (LPS-induced or not-induced). The results showed SP-2 depolymerized into homogeneous and controllable-size oligosaccharide products. The depolymerized ratio can reach 80%. The results of the measurement of reducing sugars indicate that SP-2 was cleaved from within the sugar chain. The SP-2 was deduced to have a monosaccharide sequence of GlcN-Man-Man-Man-Man-Man based on the digested fragment information. The depolymerization product restrained the release of NO and the accumulation of ROS. By testing the RAW264.7 cell scratch assay, it was found that it enhances the migration of immune cells. DBD degradation of SP-2 leads to homogeneous and controllable-size oligosaccharide products, and this technique can be used for polysaccharide structure analysis. The depolymerized product of SP-2 has an anti-inflammatory capability in vitro.

Design of Hollow Porous P-NiCo2O4@Co3O4 Nanoarray and Its Alkaline Aqueous Zinc-Ion Battery Performance.

Alkaline aqueous zinc-ion batteries possess a wider potential window than those in mildly acidic systems; they can achieve high energy density and are expected to become the next generation of energy storage devices. In this paper, a hollow porous P-NiCo2O4@Co3O4 nanoarray is obtained by ion etching and the calcination and phosphating of ZiF-67, which is directly grown on foam nickel substrate, as a precursor. It exhibits excellent performance as a cathode material for alkaline aqueous zinc-ion batteries. A high discharge specific capacity of 225.3 mAh g-1 is obtained at 1 A g-1 current density, and it remains 81.9% when the current density is increased to 10 A g-1. After one thousand cycles of charging and discharging at 3 A g-1 current density, the capacity retention rate is 88.8%. Even at an excellent power density of 25.5 kW kg-1, it maintains a high energy density of 304.5 Wh kg-1. It is a vital, promising high-power energy storage device for large-scale applications.

Geographical origin determination of Red Huajiao in China using the electronic nose combined with ensemble recognition algorithm.

Red Huajiao was the most important Zanthoxylum species in China, and its quality was highly determined the geographical region. This study was aimed to establish a determination method for the geographical origin recognition of Red Huajiao by using the electronic nose and ensemble recognition algorithm. Six origins of samples were detected by the electronic nose, and two categories of electronic nose sensors characteristic values, named as "optimized characteristic value" and "filtered characteristic value," were obtained by the principal component analysis and discrimination index method and Filter-Wrapper method. Based on the two categories of characteristic values, 22 kinds of model analysis methods, which belonged to five categories of ensemble recognition algorithms were used to recognize the geographical origin. The total recognition accuracy rate of the two categories of characteristic values were 83.9% and 85.7%, respectively. Furthermore, during 22 kinds of model analysis method, the ensemble Subspace KNN and Bagged Trees methods in Ensemble Learning algorithm exhibited the best distinguishing ability with the accuracy rate more than 90%. Therefore, the electronic nose combined with Ensemble Learning would be promising for the geographical origin determination application. PRACTICAL APPLICATION: This work demonstrates that the Red Huajiao can be simply and rapidly determined by using electronic nose combined with ensemble recognition algorithm, allowing to effectively distinguish geographical origin of Red Huajiao, which can provide an important reference for the quality assessment of Huajiao.

An optimized organic acid human sensory sourness analysis method.

BACKGROUND: Sour taste perception builds on both chemical and physiological foundations, and plays an important role in food flavor, including that of fruit, beer, wine, and other beverages. A uniform sourness standard and sourness conversion method for researchers and food enterprises is necessary to obtain uniform conclusions. RESULTS: This study established an optimized organic acid sensory sourness analysis and sourness conversion method. It is based on sour sensory difference strength curves, which consist of an absolute threshold value and sensory difference threshold values. Defining the absolute threshold value of citric acid sourness as 1, sourness could be calculated according to the curve. With a logarithmic curve form, the acid sourness indexes (AI) were calculated as 1, 0.74, 0.77, 1.31, and 1.21 for citric, malic, fumaric, lactic, and tartaric acid samples, respectively. Consequently, each acid's sourness and concentration could be obtained and converted. Single acid and mixed acid sourness comparison evaluation's result implied that the novel method was more accurate (91.7-100%) than the hydrogen ion concentration method. CONCLUSION: The novel sourness determination and conversion equation would provide more accurate sourness standard and calculation method in food sensory areas. © 2021 Society of Chemical Industry.

Analysis and prediction of drug-drug interaction by minimum redundancy maximum relevance and incremental feature selection.

Drug-drug interaction (DDI) defines a situation in which one drug affects the activity of another when both are administered together. DDI is a common cause of adverse drug reactions and sometimes also leads to improved therapeutic effects. Therefore, it is of great interest to discover novel DDIs according to their molecular properties and mechanisms in a robust and rigorous way. This paper attempts to predict effective DDIs using the following properties: (1) chemical interaction between drugs; (2) protein interactions between the targets of drugs; and (3) target enrichment of KEGG pathways. The data consisted of 7323 pairs of DDIs collected from the DrugBank and 36,615 pairs of drugs constructed by randomly combining two drugs. Each drug pair was represented by 465 features derived from the aforementioned three categories of properties. The random forest algorithm was adopted to train the prediction model. Some feature selection techniques, including minimum redundancy maximum relevance and incremental feature selection, were used to extract key features as the optimal input for the prediction model. The extracted key features may help to gain insights into the mechanisms of DDIs and provide some guidelines for the relevant clinical medication developments, and the prediction model can give new clues for identification of novel DDIs.

Prediction of bioactive compound pathways using chemical interaction and structural information.

The functional screening of compounds is an important topic in chemistry and biomedicine that can uncover the essential properties of compounds and provide information concerning their correct use. In this study, we investigated the bioactive compounds reported in Selleckchem, which were assigned to 22 pathways. A computational method was proposed to identify the pathways of the bioactive compounds. Unlike most existing methods that only consider compound structural information, the proposed method adopted both the structural and interaction information from the compounds. The total accuracy achieved by our method was 61.79% based on jackknife analysis of a dataset of 1,832 bioactive compounds. Its performance was quite good compared with that of other machine learning algorithms (with total accuracies less than 46%). Finally, some of the false positives obtained by the method were analyzed to investigate the likelihood of compounds being annotated to new pathways.

Leveraging user query sessions to improve searching of medical literature.

Published reports about searching medical literature do not refer to leveraging the query context, as expressed by previous queries in a session. We aimed to assess novel strategies for context-aware searching, hypothesizing that this would be better than baseline. Building upon methods using term frequency-inverse document frequency, we added extensions such as a function incorporating search results and terms of previous queries, with higher weights for more recent queries. Among 60 medical students generating queries against the TREC 9 benchmark dataset, we assessed recall and mean average precision. For difficult queries, we achieved improvement (27%) in average precision over baseline. Improvements in recall were also seen. Our methods outperformed baseline by 4% to 14% on average. Furthermore, the effectiveness of context-aware search was greater for longer query sessions, which are typically more challenging. In conclusion, leveraging the previous queries in a session improved overall search quality with this biomedical database.

Induction of apoptosis in glioma cells and upregulation of Fas expression using the human interferon-ß gene.

We investigated whether IFN-ß inhibits the growth of human malignant glioma and induces glioma cell apoptosis using the human IFN-ß gene transfected into glioma cells. A eukaryonic expression vector (pSV2IFNß) for IFN-ß was transfected into the glioma cell line SHG44 using liposome transfection. Stable transfection and IFN-ß expression were confirmed using an enzyme-linked immunosorbent assay (ELISA). Cell apoptosis was also assessed by Hoechst staining and electron microscopy. In vivo experiments were used to establish a SHG44 glioma model in nude mice. Liposomes containing the human IFN-ß gene were injected into the SHG44 glioma of nude mice to observe glioma growth and calculate tumor size. Fas expression was evaluated using immunohistochemistry. The IFN-ß gene was successfully transfected and expressed in the SHG44 glioma cells in vitro. A significant difference in the number of apoptotic cells was observed between transfected and non- transfected cells. Glioma growth in nude mice was inhibited in vivo, with significant induction of apoptosis. Fas expression was also elevated. The IFN-ß gene induces apoptosis in glioma cells, possibly through upregulation of Fas. The IFN-ß gene modulation in the Fas pathway and apoptosis in glioma cells may be important for the treatment of gliomas.